A. van der Grinten and H. Meyerhenke
Scaling Betweenness Approximation to Billions of Edges by MPI-based Adaptive Sampling
2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), New Orleans, LA, USA, May 18-22, 2020, IEEE, 2020
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E. Angriman, M. Predari, A. van der Grinten, and H. Meyerhenke
Approximation of the Diagonal of a Laplacian's Pseudoinverse for Complex Network Analysis
28th Annual European Symposium on Algorithms, ESA 2020, September 7-9, 2020, Pisa, Italy (Virtual Conference), Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020
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A. van der Grinten, E. Angriman, and H. Meyerhenke
Scaling up network centrality computations - A brief overview
it Inf. Technol., 62(34), 2020
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C. Tzovas, M. Predari, and H. Meyerhenke
Distributing Sparse Matrix/Graph Applications in Heterogeneous Clusters - an Experimental Study
27th {IEEE} International Conference on High Performance Computing, Data, and Analytics, HiPC 2020, Pune, India, December 16-19, 2020, IEEE, 2020
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E. Angriman, A. van der Grinten, A. Bojchevski, D. Zügner, S. Günnemann, and H. Meyerhenke
Group Centrality Maximization for Large-scale Graphs
Proceedings of the Symposium on Algorithm Engineering and Experiments, ALENEX 2020, Salt Lake City, UT, USA, January 5-6, 2020, SIAM, 2020
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M. F. Faraj, A. van der Grinten, H. Meyerhenke, J. L. Träff, and C. Schulz
High-Quality Hierarchical Process Mapping
CoRR, 200107134, 2020
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M. Simsek and H. Meyerhenke
Combined Centrality Measures for an Improved Characterization of Influence Spreadin Social Networks
CoRR, 200305254, 2020
arXiv eprint, RIS, BibTex